Capacity planning tools can be used to plan the capacity of a computer system and manage its performance. To do this, capacity planning tools focus on (1) identifying performance bottlenecks in the computer system and (2) providing “what-if’ functionalities that can be used to evaluate performance implications of different hardware configurations of that system. Other tools referred to as system provisioning tools can be used to provision the computer system with the goal of setting up a configuration that is cost effective from a business perspective. To effectively achieve this goal, provisioning tools need intelligent input to determine what and how many servers and other system components are needed to satisfy the service level objectives (SLOs) of the computer system.
Unfortunately, prior art capacity planning tools do not provide direct input to provisioning tools, nor do they receive any direct feedback from the provisioned computer system that could be used to validate or adjust the system's configuration. Instead, users have to translate performance information, such as reports and graphs, into system recommendations and then input those recommendations into the provisioning tool for execution because direct output from the prior art capacity planning tool would not be usable by the prior art provisioning tool. Due to these problems, prior art provisioning tools provision a computer system based merely on user-inputted rules or on rule of thumb. Moreover, prior art provisioning tools rely on policies that are static and that may or may not reflect historical demands of the computer system for resources. In short, prior art provisioning tools do not take provisioning actions on potential computing needs based on historic resource usage patterns. They are purely reactive rather than proactive.